Exploration on OCT biomarker candidate related to macular edema caused by diabetic retinopathy and retinal vein occlusion in SD-OCT images.

To improve the understanding of potential pathological mechanisms of macular edema (ME), we try to discover biomarker candidates related to ME caused by diabetic retinopathy (DR) and retinal vein occlusion (RVO) in spectral-domain optical coherence tomography images by means of deep learning (DL). 32 eyes of 26 subjects with non-proliferative DR (NPDR), 77 eyes of 61 subjects with proliferative DR (PDR), 120 eyes of 116 subjects with branch RVO (BRVO), and 17 eyes of 15 subjects with central RVO (CRVO) were collected. A DL model was implemented to guide biomarker candidate discovery.

Controllable editing via diffusion inversion on ultra-widefield fluorescein angiography for the comprehensive analysis of diabetic retinopathy.

By incorporating multiple indicators that facilitate clinical decision making and effective management of diabetic retinopathy (DR), a comprehensive understanding of the progression of the disease can be achieved. However, the diversity of DR complications poses challenges to the automatic analysis of various information within images. This study aims to establish a deep learning system designed to examine various metrics linked to DR in ultra-widefield fluorescein angiography (UWFA) images.

Risk Factors and Management of Intraocular Pressure Elevation After Vitrectomy Combined with Silicone Oil Tamponade.

Silicone oil has emerged as the common option for intraocular tamponade during complicated retina vitrectomy. However, the postoperative elevation of intraocular pressure (IOP), influenced by numerous factors, remains a significant and frequently encountered complication that poses a potential threat to vision. Extensive research has been conducted to investigate the risk factors associated with elevated IOP following silicone oil tamponade, including silicone oil viscosity, preoperative high IOP, diabetes, and lens status.